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Record W4417336218 · doi:10.1080/09581596.2025.2598985

‘The benefits do not reach us’: analyzing the discrepancies between the state recognition of hijra and their reality in Dhaka, Bangladesh

2025· article· en· W4417336218 on OpenAlexfundno aff
Samira Dishti Irfan, Masud Reza, Mohammad Niaz Morshed Khan, Rakibul Hassan, Sharful Islam Khan

Bibliographic record

VenueCritical Public Health · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
FundersInternational Centre for Diarrhoeal Disease Research, BangladeshGlobal Affairs Canada
KeywordsThematic analysisDeclarationFocus groupGovernment (linguistics)Sexual and reproductive health and rightsQualitative researchQualitative propertyStigma (botany)

Abstract

fetched live from OpenAlex

Hijra, a transgender group in Bangladesh, despite being acknowledged by the government in 2013 as a separate gender category, cannot adequately exercise their gender and sexual rights. This study aimed to explore discrepancies between the gender declaration and their lived realities of their gender and sexual rights. This study adopted the policy analysis framework, whilst linking it to SRHR frameworks by the Guttmacher-Lancet Commission. This study adopted desk review and mixed methods research to explore their ability to exercise their sexual and reproductive health rights as hijra. A total of 298 hijra participated in the study and completed quantitative surveys. Among them, 20 mutually exclusive groups of participants also completed 20 in-depth interviews and five focus groups (of 4-5 participants, totaling 20-25 participants). Data were analyzed through descriptive statistics and thematic analysis. The findings indicated that 79.2% obfuscated their hijra identity, 89.8% of whom hid from their family. Of the participants, 80.9% hid their partners due to fear of stigma and 82.2% reported societal discrimination. Almost all participants (98.7%) reported gender-based discrimination. The qualitative findings revealed motifs of exclusion and forced duplicity emerged where hijra disguised their identities, denied services, and faced gender-based discrimination in various settings including healthcare, education and employment. Legal recognition is a crucial step in improving health and quality of life for hijra, however, much work remains to advance their SRHR such as advocacy, cultural competency training of institutional service providers, and community mobilization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.416
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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